PAGE 2026 workshop: Mastering covariate modeling – hands-on with the Full Random Effects Model (FREM) approach
This workshop provides theoretical insights and hands-on training (using R, NONMEM, and PsN) in applying the Full Random Effects Model (FREM) to integrate covariate data into your modeling process effectively for robust decision-making in pharmacometrics.
Note: This event has passed. For upcoming events, please visit the Events page.
Satellite meeting overview
Join us for an interactive one-day workshop, June 2, in connection with PAGE 2026. This workshop dives deep into the FREM methodology. Participants will gain practical experience using FREM to assess how different factors affect model predictions and ultimately drive decision-making in drug development. The session will also include hands-on exercises where participants will implement FREM in real-world case studies, reinforcing learning and building confidence in using this approach for model-based decision support metrics.
Key topics covered
- Fundamentals of the FREM methodology and how to use it for assessing covariate impacts in pharmacometric models.
- Model-based decision-making techniques using FREM.
- Hands-on implementation of FREM in pharmacometrics.
- Interpretation and application of FREM results in real-world drug development.
Learning objectives
By the end of this workshop, participants will:
- Understand the fundamentals of the FREM methodology.
- Gain hands-on experience implementing FREM for model-based decision-making in various pharmacometric contexts.
- Learn to interpret and apply FREM results to improve modeling and decision-making processes.